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. 2013 Sep;184(1):42-48.e3.
doi: 10.1016/j.jss.2013.03.064. Epub 2013 Apr 16.

Assessing clinical discharge data preferences among practicing surgeons

Ira L Leeds  1 , Vjollca Sadiraj, James C Cox, Kurt E Schnier, John F Sweeney
Affiliations

Assessing clinical discharge data preferences among practicing surgeons

Ira L Leeds et al. J Surg Res. 2013 Sep.

Abstract

Background: It is believed that many postoperative patient readmissions can be curbed via optimization of a patient's discharge from hospital, but little is known about how surgeons make the decision to discharge a patient. This study explored the criteria that surgeons preferentially value in their discharge decision-making process.

Materials and methods: All surgical faculty and residents at a U.S. academic medical center were surveyed about the relative importance of specific criteria regularly used to make a discharge decision. Demographic and professional information was collected about each surgeon as well. A Kruskal-Wallis and Fisher's exact test were used to describe one-way analysis of variance between groupings of surgeons. Ordered logit regressions were used to analyze variations across multiple subgroups. Factor analysis was used to further characterize statistically relevant groupings of criteria.

Results: In total, 88 (49%) of the invited surgeons responded to the survey. Respondents reported statistically less reliance on common Laboratory tests and Patient demographics when making discharge decisions preferring Vital signs, Perioperative factors, and Functional criteria. Surgeon-specific factors that influenced discharge criteria preferences included years of clinical education and gender. Factor analysis further identified subtle variations in preferences for specific criteria groupings based on clinical education, gender, and race.

Conclusions: Surgeons use a wide range of clinical data when making discharge decisions. Typical measures of patient condition also appear to be used heterogeneously with a preference for binary rather than continuous measures. Further understanding the nature of these preferences may suggest novel ways of presenting discharge-relevant information to clinical decision makers to optimize discharge outcomes.

Keywords: Clinical decision-making; Decision support; Discharge; Hospital readmission; Ordered logit regression; Surgical outcomes.

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Figures

Figure 1
Figure 1. Median Likert Scale Rating, All Surveyed Clinical Factors (n=81)
Means follow variable names; standard deviations in brackets.
See this image and copyright information in PMC

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